Müllerian Duct Anomalies and Mimics in Children and Adolescents: Correlative Intraoperative Assessment with Clinical Imaging
Bibliographic record
Abstract
Müllerian duct anomalies (MDAs) are congenital entities that result from nondevelopment, defective vertical or lateral fusion, or resorption failure of the müllerian (paramesonephric) ducts. MDAs are common, although the majority are asymptomatic, and have been classified by the American Society of Reproductive Medicine according to clinical manifestations, prognosis, and treatment. Accurate diagnosis of an MDA is essential, since the management approach varies depending on the type of malformation. In females, when a müllerian duct becomes obstructed, the patient may present with an abdominal mass and dysmenorrhea. If the patient is not treated in a timely fashion, the consequences can be severe, extending even to infertility. When an MDA is suspected, ultrasonography (US) should be performed initially to delineate any abnormalities in the genital tract. However, US cannot help identify the type of MDA. In contrast, magnetic resonance imaging is a valuable technique for noninvasive evaluation of the female pelvic anatomy and accurate MDA classification. If obstruction is present, surgical correction of the MDA may be required, and further counseling of the patient with regard to reproductive possibilities becomes important. Supplemental material available at http://radiographics.rsnajnls.org/cgi/content/full/29/4/1085/DC1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".